Can the Past be Prologue? NCHRP 17-67 Results: Can the Past be Prologue? Robert C. Wunderlich Center for Transportation Safety Texas A&M Transportation Institute

NCHRP 17-67 Team

Likelihood of Fatality per Unit of Travel Key Components Fatalities Exposure Risk Measure of Travel Likelihood of Fatality per Unit of Travel

Exposure Measure

Constant Risk or VMT vs Total Fatalities Actually, these are all the same units: Fatalities The graphs show what the fatalities would be if risk was constant and only VMT had varied: orange line If VMT was constant and only risk had varied: Teal Line And the actual

Safety and Capital Expenditures? What caused risk to decrease? Economic Factors? Safety and Capital Expenditures? Safety Regulations? Vehicle Safety?

Economic GDP per Capita % Unemployment for 16-24 year olds Rural VMT Beer Consumption Median Income

Safety & Capital Expenditures Per highway mile Law enforcement Education Safety-related Capital HSIP Obligations Capital Improvements

Occupant Restraint Laws Safety Regulations Ratings for: DUI laws Helmet laws Occupant Restraint Laws

Vehicle Safety Percent of Vehicle Fleet 1991 or newer Am only showing most significant factors. Will note in presentation

Models Negative Binomial Regression Model Controlling for State Effects – MCS Adjusts for the effects of state-associated unknown influences not considered in the model. Model Not Controlling for State Effects – MNCS Does not make a separate adjustment for other influences. change model removes overall differences between states on all variables. Large states may have larger numbers of fatalities, larger expenditures, and larger numbers of miles driven, but change in those states is proportional. Small states do, however, produce more volatile change values because of the smaller samples. Change Model Data translated into percent change from year to year within each state

F𝑎𝑡𝑎𝑙𝑖𝑡𝑖𝑒𝑠=VMT× 𝑒 𝛽 0 + 𝑖 𝛽 𝑖 𝑋 𝑖 Negative Binomial Regression Model Forms MCS 𝐹𝑎𝑡𝑎𝑙𝑖𝑡𝑖𝑒𝑠=VMT× 𝑒 𝛽 0 + 𝛾 𝑠 + 𝑖 𝛽 𝑖 𝑋 𝑖 MNCS F𝑎𝑡𝑎𝑙𝑖𝑡𝑖𝑒𝑠=VMT× 𝑒 𝛽 0 + 𝑖 𝛽 𝑖 𝑋 𝑖 I think I have the models correct now, please verify Fatalities = VMT x Risk Risk = 𝑒 𝛽 0 + 𝑖 𝛽 𝑖 𝑋 𝑖

Modeling Results MNCS Model Prediction MCS Model Prediction Observed

Economic Factors Economic Factors MCS Model Prediction

& Capital Expenditures Modeling Results I am not labeling everything because I want to emphasize the difference made by the addition of the new factors. I think the progression will be clear in the presentation. + Safety & Capital Expenditures

Modeling Results + Safety Regulations

Modeling Results + Vehicle Safety Observed

Most Significant Variables Negative Binomial Most Significant Variables ≈ 85% Economic % Unemployment for 16-24 year olds GDP per Capita Median Income Beer Consumption ≈ 12% ≈ 2 to 3 % Vehicle Safety Percent of Vehicle Fleet 1991 or newer Safety Regulations DUI laws 16 to 24 year old unemployment is 50 to 60% of total predicted decline Unemployment for this group was twice the national average And this group accounted for about half of the reduction in fatalities over this periodl The insurance and car rental companies are right.

Change Model Decrease Accounted for: 58% 16-24 Year Old Unemployment 29% GDP and Median Income 16%

Takeaways Both VMT and Risk varied over the study period. It’s complicated: Steady Safety Progress Abrupt Economic Influences Economic factors clearly affect : VMT and Risk All VMT (Driving) is not created equal from a risk perspective Factors beyond the control of transportation professionals can have a large influence on traffic safety.

Aggregated Data is lacking Implications for Safety Management Safety Goal Setting Can the Models help? Despite advances in safety prediction tools and effectiveness of countermeasures: Aggregated Data is lacking On point 3, do not disagree—I think the reference is mainly to state DOT programs? At the same time, it would be good to emphasize that there are a lot of effective tools within the scope of safety professionals that are proven to be effective (belts, crashworthiness, laws to improve safe driving behavior, crashworthy roads, etc.). We know we have effective countermeasures Evaluation and Tracking are needed at the state level.